Therapeutic strategies and predictive models for Xp11.2 translocation/TFE3 gene fusion renal cell carcinoma in adults based on data of two Chinese medical centers

Abstract

Objective: This study aims to establish an effective predictive model for predicting Xp11.2 translocation/TFE3 gene fusion renal cell carcinoma (TFE3-RCC) and develop optimal therapeutic strategies.

Methods: Data from 4961 patients diagnosed with renal cell carcinoma at two medical centers in China were retrospectively analyzed. A cohort of 1571 patients from Zhejiang Provincial People's Hospital (Ra cohort) was selected to construct the model. Another cohort of 1124 patients from the Second Affiliated Hospital of Zhejiang Chinese Medical University was used for external validation (the Ha cohort). All patients with TFE3-RCC in both cohorts were included in the Ta cohort for the prognostic analysis. Univariate and multivariate binary logistic regression analyses were performed to identify independent predictors of the predictive nomogram. The apparent performance of the model was validated. Decision curve analysis was also performed to assess the clinical utility of the developed model. Factors associated with progression and prognosis in the Ta cohort were analyzed using the log-rank method, and Cox regression analysis and Kaplan-Meier survival curves were used to describe the effects of factors on prognosis and progression.

Results: Univariate and multivariate logistic regression analyses demonstrated that age, sex, BMI, smoking, eosinophils, and LDL were independent predictors of TFE3-RCC. Therefore, a predictive nomogram for TFE3-RCC, which had good discriminatory power (AUC = 0.796), was constructed. External validation (AUC = 0.806) also revealed good predictive ability. The calibration curves displayed good consistency between the predicted and observed incidences of TFE3-RCC. Invasion of regional lymph nodes, tyrosine kinase inhibitors, and surgical methods were independent factors associated with progression. Tyrosine kinase inhibitors are independent prognostic factors.

Conclusion: This study not only proposed a high-precision clinical prediction model composed of various variables for the early diagnosis of Xp11.2 translocation/TFE3 gene fusion renal cell carcinoma but also optimized therapeutic strategies through prognostic analysis.

Keywords: TFE3-RCC; Xp11.2 translocation; predict; prognosis; rare cancer.

Figure 1

Enrollment process.

Figure 2

Diagnostic nomogram. An accurate TFE3-RCC diagnostic nomogram constructed using age, sex, BMI, smoking, eosinophil count, and LDL level.

Figure 3

Calibration curve and ROC curve. Discrimination of the nomogram was evaluated by the ROC curve, AUC = 0.796 in the Ra cohort (A), AUC = 0.806 in the Ha cohort (B); calibration curves illuminate the agreement between the predicted risks of TFE3-RCC (C) and the observed incidence of TFE3-RCC (D). The dotted line represents the ideal flawless model.

Figure 4

Decision curve analysis. DCA curve analysis of the training cohort (A) and external validation (B). Quantified net benefits were measured for different threshold probabilities. The y-axis denotes the standardized net benefit, and the x-axis denotes the threshold probabilities. The red line represents our nomogram, the blue line represents the condition of patients with TFE3-RCC, and the black line represents the condition of which none suffered from TFE3-RCC.

Figure 5

Representative images of TFE3 immunohistochemical staining and microscopic appearance for Xp11.2 RCC. (A) Blood sinusoid and Psammoma bodies were abundant in intercellular substance. The arrow points to Psammoma bodies; (B) abundant and deeply stained eosinophile cytoplasm, similar to renal clear cell carcinoma; (C) the results of immunohistochemistry showed that TFE3 was strongly positive in cancerous tissue; (D) FISH test results: 100 cells were counted, and the number of cells with TFE3 gene breakage was more than 20. TFE3 gene probe: Broken (positive).

Figure 6

Contrast-enhanced computed tomography results of postoperative follow-up in a patient with TFE3-RCC. (A) The results of re-examination one month after the surgery; (B) three months after surgery, the patient’s re-examination showed multiple tumor metastases in the abdominal wall, left psoas major muscle, and pelvic cavity, so the patient started sunitinib therapy; (C) the re-examination results at six months after surgery showed that the metastasis was smaller than before, and the disease progression was controlled.

Figure 7

Kaplan-Meier analysis for progression-free survival and overall survival in the Ta cohort. (A) The effect of TKI on progression; (B) the effect of regional lymph node invasion on progression; (C) the effect of surgical methods on progression; (D) the effect of TKI on prognosis.